Numerical simulation of multiphase multi-physics flow in underground reservoirs: Frontiers and challenges
Abstract view|105|times PDF download|10|times
Abstract
This paper explores significant advancements in the numerical simulation of multiphase, multi-physics flows within underground reservoirs, driven by the necessity to understand and manage complex geological and engineered systems. It delves into the latest research in numerical simulation techniques at both the pore and Darcy scales, emphasizing the integration of traditional methods with emerging machine learning technologies. Key simulation methods reviewed at the pore scale include the lattice Boltzmann method, level set method, phase field method, and volume of fluid method, each offering unique advantages and facing limitations related to computational efficiency and stability. Special attention is given to spontaneous imbibition, where capillary action facilitates the movement of wetting fluids into porous media. Discussions at the Darcy scale focus on macroscopic simulation methods that simplify microscale interactions but face challenges in accurately modeling the multiscale and heterogeneous nature of fractured media. Furthermore, an overview of the basic principles, limitations, and potential of integrating machine learning algorithms with traditional numerical methods emphasizes their role in enhancing simulation efficiency and stability. Future research will aim to address existing challenges and maximize the use of advanced computational technologies to refine the accuracy, efficiency, and practical applicability of multiphase and multifield flow simulations in underground reservoirs.
Document Type: Current minireview
Cited as: Liu, P., Zhao, J., Li, Z., Wang, H. Numerical simulation of multiphase multi-physics flow in underground reservoirs: Frontiers and challenges. Capillarity, 2024, 12(3): 72-79. https://doi.org/10.46690/capi.2024.09.02
Keywords
Full Text:
PDFReferences
Ahammad, M. J., Alam, J. M., Rahman, M., et al. Numerical simulation of two-phase flow in porous media using a wavelet based phase-field method. Chemical Engineering Science, 2017, 173: 230-241.
Cai, J., Jin, T., Kou, J., et al. Lucas-washburn equation-based modeling of capillary-driven flow in porous systems. Langmuir, 2021, 37(5): 1623-1636.
Cai, J., Perfect, E., Cheng, C. L., et al. Generalized modeling of spontaneous imbibition based on Hagen–Poiseuille flow in tortuous capillaries with variably shaped apertures. Langmuir, 2014, 30(18): 5142-5151.
Carciofi, B. A., Prat, M., Laurindo, J. B. Homogeneous volume-of-fluid (vof) model for simulating the imbibition in porous media saturated by gas. Energy & fuels, 2011, 25(5): 2267-2273.
Chan, S., Elsheikh, A. H. A machine learning approach for efficient uncertainty quantification using multiscale methods. Journal of Computational Physics, 2018, 354: 493-511.
Chen, L., He, A., Zhao, J., et al. Pore-scale modeling of complex transport phenomena in porous media. Progress in Energy and Combustion Science, 2022, 88: 100968.
Chukwudozie, C., Bourdin, B., Yoshioka, K. A variational phase-field model for hydraulic fracturing in porous media. Computer Methods in Applied Mechanics and Engineering, 2019, 347: 957-982.
Eshghinejadfard, A., Dar´ oczy, L., Janiga, G., et al. Calculation of the permeability in porous media using the lattice boltzmann method. International Journal of Heat and Fluid Flow, 2016, 62: 93-103.
Fei, L., Qin, F., Wang, G., et al. Coupled lattice boltzmann method-discrete element method model for gas–liquid–solid interaction problems. Journal of Fluid Mechanics, 2023, 975: A20.
Fleissner, F., Gaugele, T., Eberhard, P. Applications of the discrete element method in mechanical engineering. Multi body System Dynamics, 2007, 18: 81-94.
Guo, L., Younes, A., Fahs, M., et al. An efficient fully crouzeix-raviart finite element model for coupled hydromechanical processes in variably saturated porous media. Advances in Water Resources, 2024, 186: 104663.
Hatiboglu, C. U., Babadagli, T. Pore-scale studies of spontaneous imbibition into oil-saturated porous media. Physical Review E, 2008, 77(6): 066311.
Heil, M. An efficient solver for the fully coupled solution of large-displacement fluid–structure interaction problems. Computer Methods in Applied Mechanics and Engineering, 2004, 193(1-2): 1-23.
Herreros, M., Mabssout, M., Pastor, M. Application of level set approach to moving interfaces and free surface problems in flow through porous media. Computer Methods in Applied Mechanics and Engineering, 2006, 195(1-3): 1-25.
Izadi, G., Elsworth, D. The influence of thermal-hydraulic-mechanical-and chemical effects on the evolution of per meability, seismicity and heat production in geothermal reservoirs. Geothermics, 2015, 53: 385-395.
Kim, J., Tchelepi, H. A., Juanes, R. Stability and convergence of sequential methods for coupled flow and geomechan ics: Drained and undrained splits. Computer Methods in Applied Mechanics and Engineering, 2011a, 200(23-24): 2094-2116.
Kim, J., Tchelepi, H. A., Juanes, R. Stability and convergence of sequential methods for coupled flow and geomechanics: Fixed-stress and fixed-strain splits. Computer Methods in Applied Mechanics and Engineering, 2011b, 200(13-16): 1591-1606.
Li, Y., Zhang, T., Sun, S. Acceleration of the nvt flash calculation for multicomponent mixtures using deep neural network models. Industrial & Engineering Chemistry Research, 2019, 58(27): 12312-12322.
Li, Z., Zheng, H., Kovachki, N., et al. Physics-informed neural operator for learning partial differential equations. ACM/JMS Journal of Data Science, 2021, 3(1): 1-27.
Liu, H., Kang, Q., Leonardi, C. R., et al. Multiphase lattice boltzmann simulations for porous media applications: A review. Computational Geosciences, 2016, 20: 777-805.
Liu P., Yan X., Yao J., et al. Modeling and analysis of the acidizing process in carbonate rocks using a two-phase thermal-hydrologic-chemical coupled model. Chemical Engineering Science, 2019, 207: 215-234.
Liu, P., Kong, X., Feng, G., et al. Three-dimensional simulation of wormhole propagation in fractured-vuggy carbonate rocks during acidization. Advances in Geo-Energy Research, 2023, 7(3): 199-210.
Liu, Y., Berg, S., Ju, Y., et al. Systematic investigation of corner flow impact in forced imbibition. Water Resources Research, 2022, 58(10): e2022WR032402.
Liu, Z., Yang, Y., Zhang, Q., et al. Pore-scale simulation of fracture propagation by CO2 flow induced in deep shale based on hydro-mechanical coupled model. SPE Journal, 2024, 29(2): 1210-1225.
Lowrie, R. B. A comparison of implicit time integration methods for nonlinear relaxation and diffusion. Journal of Computational Physics, 2004, 196(2): 566-590.
Mahmood, M. N., Nguyen, V., Guo, B. Challenges in mathematical modeling of dynamic mass transfer controlled by capillary and viscous forces in spontaneous fluid imbibition processes. Capillarity, 2024, 11(2): 53-62.
McDermott, C., Bond, A., Harris, A. F., et al. Application of hybrid numerical and analytical solutions for the simulation of coupled thermal, hydraulic, mechanical and chemical processes during fluid flow through a fractured rock. Environmental Earth Sciences, 2015, 74(12): 7837-7854.
Meakin, P., Tartakovsky, A. M. Modeling and simulation of pore-scale multiphase fluid flow and reactive transport in fractured and porous media. Reviews of Geophysics, 2009, 47(3): RG3002.
Qin, F., Mazloomi Moqaddam, A., Del Carro, L., et al. Tricoupled hybrid lattice boltzmann model for nonisothermal drying of colloidal suspensions in micropore structures. Physical Review E, 2019, 99(5): 053306.
Taron, J., Elsworth, D., Min, K. B. Numerical simulation of thermal-hydrologic-mechanical-chemical processes in deformable, fractured porous media. International Journal of Rock Mechanics and Mining Sciences, 2009, 46(5): 842-854.
Viswanathan, H. S., Ajo-Franklin, J., Birkholzer, J. T., et al. From fluid flow to coupled processes in fractured rock: Recent advances and new frontiers. Reviews of Geophysics, 2022, 60(1): e2021RG000744.
Wang, H., Cai, J., Su, Y., et al. Imbibition behaviors in shale nanoporous media from pore-scale perspectives. Capillarity, 2023a, 9(2): 32-44.
Wang N., Chang H., Zhang D., Surrogate and inverse modeling for two-phase flow in porous media via theory-guided convolutional neural network. Journal of Computational Physics, 2022, 466: 111419.
Wang, W., Xie, Q., An, S., et al. Pore-scale simulation of multiphase flow and reactive transport processes involved in geologic carbon sequestration. Earth-Science Reviews, 2023b: 104602.
Wen, G., Li, Z., Long, Q., et al. Real-time high-resolution CO2 geological storage prediction using nested fourier neural operators. Energy & Environmental Science, 2023, 16(4): 1732-1741.
Yan, X., Huang, Z., Yao, J., et al. An efficient embedded discrete fracture model based on mimetic finite difference method. Journal of Petroleum Science and Engineering, 2016, 145: 11-21.
Yao, J., Zhang, X., Sun, Z., et al. Numerical simulation of the heat extraction in 3D-egs with thermal-hydraulic-mechanical coupling method based on discrete fractures model. Geothermics, 2018, 74: 19-34.
Zahasky, C., Benson, S. M. Spatial and temporal quantification of spontaneous imbibition. Geophysical Research Letters, 2019, 46(21): 11972-11982.
Zhang, K., Zuo, Y., Zhao, H., et al. Fourier neural operator for solving subsurface oil/water two-phase flow partial differential equation. SPE Journal, 2022, 27(03): 1815-1830.
Zhang, N., Yao, J., Xue, S., et al. Multiscale mixed finite element, discrete fracture–vug model for fluid flow in fractured vuggy porous media. International Journal of Heat and Mass Transfer, 2016, 96: 396-405.
Zheng, H., Liu, F., Li, C. Primal mixed solution to unconfined seepage flow in porous media with numerical manifold method. Applied Mathematical Modelling, 2015, 39(2): 794-808.
Zhou, Y., Guan, W., Zhao, C., et al. Numerical methods to simulate spontaneous imbibition in microscopic pore structures: A review. Capillarity, 2024, 11(1): 1-21.
Refbacks
- There are currently no refbacks.
Copyright (c) 2024 The Author(s)
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.